Quantum machine learning and quantum biomimetics: A perspective

Lamata, Lucas (2020) Quantum machine learning and quantum biomimetics: A perspective. Machine Learning: Science and Technology, 1 (3). 033002. ISSN 2632-2153

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Abstract

Quantum machine learning has emerged as an exciting and promising paradigm inside quantum technologies. It may permit, on the one hand, to carry out more efficient machine learning calculations by means of quantum devices, while, on the other hand, to employ machine learning techniques to better control quantum systems. Inside quantum machine learning, quantum reinforcement learning aims at developing 'intelligent' quantum agents that may interact with the outer world and adapt to it, with the strategy of achieving some final goal. Another paradigm inside quantum machine learning is that of quantum autoencoders, which may allow one for employing fewer resources in a quantum device via a training process. Moreover, the field of quantum biomimetics aims at establishing analogies between biological and quantum systems, to look for previously inadvertent connections that may enable useful applications. Two recent examples are the concepts of quantum artificial life, as well as of quantum memristors. In this Perspective, we give an overview of these topics, describing the related research carried out by the scientific community.

Item Type: Article
Subjects: Science Global Plos > Multidisciplinary
Depositing User: Unnamed user with email support@science.globalplos.com
Date Deposited: 30 Jun 2023 04:47
Last Modified: 01 Nov 2023 05:34
URI: http://ebooks.manu2sent.com/id/eprint/1262

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